MERAL Myanmar Education Research and Learning Portal
Item
{"_buckets": {"deposit": "a60883e0-6974-439c-af71-ff845e39769e"}, "_deposit": {"id": "5019", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "5019"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5019", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Dynamic Replication Management Scheme for Cloud Storage", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, replication technique is widely used in datacenter storage systems to prevent data loss. Datapopularity is a key factor in data replication as popularfiles are accessed most frequently and then they becomeunstable and unpredictable. Moreover, replicasplacement is one of key issues that affect the performanceof the system such as load balancing, data locality etc.Data locality is a fundamental problem to data-parallelapplications that often happens (i.e., a data block shouldbe copied to the processing node when a processing nodedoes not possess the data block in its local storage), andthis problem leads to the decrease in performance. Toaddress these challenges, this paper proposes a dynamicreplication management scheme based on data popularityand data locality; it includes replica allocation andreplica placement algorithms. Data locality, diskbandwidth, CPU processing speed and storage utilizationare considered in the proposed data placement algorithmin order to achieve better data locality and loadbalancing effectively. Our proposed scheme will beeffective for large-scale cloud storage."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Replication"}, {"interim": "Data Popularity"}, {"interim": "Data Locality"}, {"interim": "Storage Utilization"}, {"interim": "Disk Bandwidth"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-16"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "icait2017.pdf", "filesize": [{"value": "1495 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1495000.0, "url": {"url": "https://meral.edu.mm/record/5019/files/icait2017.pdf"}, "version_id": "723a3ea2-b35c-404e-88b5-b556fa9c4d9f"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "1st International Conference on Advanced Information Technologies (ICAIT), Yangon", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thu, May Phyo"}, {"subitem_authors_fullname": "Nwe, Khine Moe"}, {"subitem_authors_fullname": "Aye, Kyar Nyo"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2017-11-01"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "978-99971-0-381-9"}, "item_title": "Dynamic Replication Management Scheme for Cloud Storage", "item_type_id": "21", "owner": "1", "path": ["1597824175385"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005019", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-16"}, "publish_date": "2019-07-16", "publish_status": "0", "recid": "5019", "relation": {}, "relation_version_is_last": true, "title": ["Dynamic Replication Management Scheme for Cloud Storage"], "weko_shared_id": -1}
Dynamic Replication Management Scheme for Cloud Storage
http://hdl.handle.net/20.500.12678/0000005019
http://hdl.handle.net/20.500.12678/0000005019284f7f86-85b4-424a-a55e-0b28e8f7a7f0
a60883e0-6974-439c-af71-ff845e39769e
Name / File | License | Actions |
---|---|---|
icait2017.pdf (1495 Kb)
|
|
Publication type | ||||||
---|---|---|---|---|---|---|
Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Dynamic Replication Management Scheme for Cloud Storage | |||||
Language | en | |||||
Publication date | 2017-11-01 | |||||
Authors | ||||||
Thu, May Phyo | ||||||
Nwe, Khine Moe | ||||||
Aye, Kyar Nyo | ||||||
Description | ||||||
Nowadays, replication technique is widely used in datacenter storage systems to prevent data loss. Datapopularity is a key factor in data replication as popularfiles are accessed most frequently and then they becomeunstable and unpredictable. Moreover, replicasplacement is one of key issues that affect the performanceof the system such as load balancing, data locality etc.Data locality is a fundamental problem to data-parallelapplications that often happens (i.e., a data block shouldbe copied to the processing node when a processing nodedoes not possess the data block in its local storage), andthis problem leads to the decrease in performance. Toaddress these challenges, this paper proposes a dynamicreplication management scheme based on data popularityand data locality; it includes replica allocation andreplica placement algorithms. Data locality, diskbandwidth, CPU processing speed and storage utilizationare considered in the proposed data placement algorithmin order to achieve better data locality and loadbalancing effectively. Our proposed scheme will beeffective for large-scale cloud storage. | ||||||
Keywords | ||||||
Replication, Data Popularity, Data Locality, Storage Utilization, Disk Bandwidth | ||||||
Identifier | 978-99971-0-381-9 | |||||
Journal articles | ||||||
1st International Conference on Advanced Information Technologies (ICAIT), Yangon | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |